What we do: We Elevate Observability
We take a modern approach to traditional observability as most of these systems are siloed and suited only for Operations. With the world acclimated to using AI, AppLogic Networks has made it its mission to serve all departments who are looking to automate, save on spending or transform their network into a business platform.
They simply want to Do More.
AppLogic Networks looks beyond what the network provides and derives new insights from the network:
- Behavioral insights (usage, adoption, engagement patterns)
- Experience insights (app QoE by user, location, tier, device)
- Sentiment insights (experience-to-satisfaction scoring)
- Trending insights (baselines, shifts, anomalies)
And when this granular data is available,network owners can apply more granular policies and traffic management to further optimize their network. This opens up a whole new world for network owners as more departments can make use of this data. For example:
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Behavioral Insights
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Can be used by Marketing teams to resell information to Advertisers or to create new premium services based how clusters of people are using the Internet
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Experience Insights
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Can be used by Customer Care groups to get ready for issues with the network
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Sentiment Insights
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Can be used by Retention groups to proactively perform outreach to customers with bad experiences.
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Trending Insights
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Can be used to create prediction models and accurately create new AI models such as propensity to churn, capacity predictions, etc.
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Network Optimization
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Can be used by Planning, Operations, and Finance teams to fix issues on the network and ultimately save.
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With this unique approach of having Best-In-Class Application Visibility and World-class Optimization, you get something beyond traditional analytics.
We call it Elevated Observability.
Elevated Observability is our approach - we identify applications from network flows, measure app-level performance, correlate it with business context (subscriber, device, tiered plans, location), and then apply AI models to derive behavior, experience, sentiment, and predictive outcomes (like churn propensity and capacity forecasting).
As a result, observability becomes usable by Product, Revenue, Care, Security teams, and more.
